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Understanding and treating brain disorders such as tremor, imbalance, and speech impairments requires deep knowledge of the cerebellum, a part of the brain that’s crucial for making accurate movements.

Scientists have long been able to eavesdrop on and record the electrical signals transmitted by neurons () in the cerebellum, allowing them to observe the signals entering and exiting this region. But the computations that the brain performs between the input and output have been largely a mystery.

However, that is now changing. A team of researchers, including those from Baylor College of Medicine, have created an artificial intelligence tool that can identify the type of neuron producing electrical signals recorded from the cerebellum during behavior, allowing a new understanding of how the cerebellum works.

Every day, people are constantly learning and forming new memories. When you pick up a new hobby, try a recipe a friend recommended or read the latest world news, your brain stores many of these memories for years or decades.

But how does your brain achieve this incredible feat?

In our newly published research in the journal Science, we have identified some of the “rules” the brain uses to learn.

Traditionally, magnetic materials have been divided into two main categories: ferromagnets and antiferromagnets. Over the past few years, however, physicists have uncovered the existence of altermagnets, a new type of magnetic material that exhibits features of both antiferromagnets and ferromagnets.

Altermagnets are that have no net magnetization (i.e., their atomic magnetic moments cancel each other out), like antiferromagnets. Yet they also break spin degeneracy (i.e., the usual energy equality between spin-up and spin-down electrons), similarly to ferromagnets.

Researchers at Songshan Lake Materials Laboratory, Southern University of Science and Technology, the Hong Kong University of Science and Technology and other institutes in China recently set out to realize a layered altermagnet that can generate non-collinear spin current. The room-temperature metallic altermagnet they unveiled was outlined in a paper published in Nature Physics.

A team of astronomers at the Space Telescope Science Institute, working with one colleague from the University of St Andrews’ Center for Exoplanet Science and another from the European Southern Observatory, has confirmed the existence of a lone black hole. In their paper published in The Astrophysical Journal, the group describes how they studied newer data regarding an object they had spotted several years ago to confirm its identity.

In 2022, members of essentially the same team reported the discovery of what they described as a “dark object” moving through the constellation Sagittarius. They suggested it might be a lone black hole. Shortly thereafter, a second research team challenged that result, suggesting it was more likely a neutron star. After continuing to study the object, the original research team has found more evidence backing up their original claim that it is likely a lone black hole.

Prior to this new finding, all the that have been identified have also had a —they are discovered due to their impact on light emitted by their companion star. Without such a companion star, it would be very difficult to see a black hole. The one identified by the team was only noticed because it passed in front of a distant non-companion star, magnifying its light and shifting its position in the sky for a short while.

Fifty years since its discovery, scientists have finally worked out how a molecular machine found in mitochondria allows us to make the fuel we need from sugars, a process vital to all life on Earth.

Scientists at the Medical Research Council (MRC) Mitochondrial Biology Unit, University of Cambridge, have worked out the structure of this machine and shown how it operates like the lock on a canal to transport pyruvate—a molecule generated in the body from the breakdown of sugars—into our mitochondria.

Known as the mitochondrial pyruvate carrier, this was first proposed to exist in 1971, but it has taken until now for scientists to visualize its structure at the using cryo-electron microscopy, a technique used to magnify an image of an object to around 165,000 times its real size. Details are published in Science Advances.

Red roses, the symbol of love, were likely yellow in the past, indicates a large genomic analysis by researchers from Beijing Forestry University, China. Roses of all colors, including white, red, pink, and peach, belong to the genus Rosa, which is a member of the Rosaceae family.

Reconstructing the ancestral traits through genomic analysis revealed that all the roads trace back to a —a single-petal flower with yellow color and seven leaflets.

The findings are published in Nature Plants.

Compared to other animal species, humans can plan and execute highly sophisticated motor tasks, including the ability to write complex characters using their hands. While many past studies have tried to better understand the neural underpinnings of handwriting and other complex human motor capabilities, these have not yet been fully elucidated.

Past studies showed that the motor cortex plays a crucial role in the human ability to translate intentions into actions. Yet the processes via which it enables the execution of precise and sequential movements, such as those associated with handwriting, are poorly understood.

Researchers at Zhejiang University in China recently carried out a study aimed at further exploring the role of the human motor cortex in the encoding of intricate handwriting, such as Chinese characters. Their findings, published in Nature Human Behavior, suggest that this encoding unfolds via a sequence of stable neural states.

Colloidal quantum dots (CQDs) are tiny semiconductor particles that are just a few nanometers in size, which are synthesized in a liquid solution (i.e., colloid). These single-crystal particles, created by breaking down bulk materials via chemical and physical processes, have proved to be promising for the development of photovoltaic (PV) technologies.

Quantum dot-based PVs could have various advantages, including a tunable bandgap, greater flexibility and solution processing. However, quantum dot-based developed so far have been found to have significant limitations, including lower efficiencies than conventional silicon-based cells and high manufacturing costs, due to the expensive processes required to synthesize conductive CQD films.

Researchers at Soochow University in China, the University of Electro-Communications in Japan and other institutes worldwide recently introduced a new method that could potentially help to improve the efficiencies of quantum-dot based photovoltaics, while also lowering their manufacturing costs. Their proposed approach, outlined in a paper published in Nature Energy, entails the engineering of lead sulfide (PbS) CQD inks used to print films for solar cells.

AI models often rely on “spurious correlations,” making decisions based on unimportant and potentially misleading information. Researchers have now discovered these learned spurious correlations can be traced to a very small subset of the training data and have demonstrated a technique that overcomes the problem. The work has been published on the arXiv preprint server.